Create app.py

app.py

@@ -0,0 +1,71 @@
+def plot_penalties():
+
+
+
+
+    # Plot the results
+    plt.clf()
+
+
+    l1_color = 'r'
+    l2_color = 'g'
+    elastic_net_color = 'b'
+
+    line = np.linspace(-1.5, 1.5, 1001)
+    xx, yy = np.meshgrid(line, line)
+
+    l2 = xx**2 + yy**2
+    l1 = np.abs(xx) + np.abs(yy)
+    rho = 0.5
+    elastic_net = rho * l1 + (1 - rho) * l2
+    fig = plt.figure(figsize=(10, 10), dpi=100)
+
+    ax = plt.gca()
+
+    elastic_net_contour = plt.contour(
+    xx, yy, elastic_net, levels=[1], colors=elastic_net_color
+    )
+    l2_contour = plt.contour(xx, yy, l2, levels=[1], colors=l2_color)
+    l1_contour = plt.contour(xx, yy, l1, levels=[1], colors=l1_color)
+    ax.set_aspect("equal")
+    ax.spines["left"].set_position("center")
+    ax.spines["right"].set_color("none")
+    ax.spines["bottom"].set_position("center")
+    ax.spines["top"].set_color("none")
+
+    plt.clabel(
+    elastic_net_contour,
+    inline=1,
+    fontsize=18,
+    fmt={1.0: "elastic-net"},
+    manual=[(-1, -1)],)
+    plt.clabel(l2_contour, inline=1, fontsize=18, fmt={1.0: "L2"}, manual=[(-1, -1)])
+    plt.clabel(l1_contour, inline=1, fontsize=18, fmt={1.0: "L1"}, manual=[(-1, -1)])
+
+    plt.tight_layout()
+    # plt.show()
+    return fig
+
+
+
+
+title = "SGD Penalties"
+
+
+with gr.Blocks(title=title) as demo:
+    gr.Markdown(f"# {title}")
+
+
+    gr.Markdown(" **[Demo is based on sklearn docs](https://scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_penalties.html#sphx-glr-auto-examples-linear-model-plot-sgd-penalties-py)**")
+
+    # greet_btn.click(fn=greet, inputs=name, outputs=output)
+    x = gr.Dropdown(["red", "blue", "green"], label="l1_color", type="index"),
+    y = gr.Dropdown(["red", "blue", "green"], label="l2_color", type="index"),
+    z = gr.Dropdown(["red", "blue", "green"], label="elastic_net_color", type="index"),
+
+    btn = gr.Button(value="Visualize SGD penalties")
+    btn.click(plot_penalties, outputs= gr.Plot() ) # 
+
+    
+
+demo.launch()